Analysis of SNP-SNP interactions and bone quantitative ultrasound parameter in early adulthood
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Correa Rodríguez, María; Viatte, Sebastien; Massey, Jonathan; Schmidt Río Valle, Jacqueline; Rueda Medina, Blanca María; Orozco Cebada, GiselaEditorial
Biomed Central
Materia
Gene interaction Quantitative ultrasound Candidate gene
Date
2017Referencia bibliográfica
Correa-Rodríguez, M.: et al. Analysis of SNP-SNP interactions and bone quantitative ultrasound parameter in early adulthood. BMC Medical Genetics, 18: 107 (2017). [http://hdl.handle.net/10481/49672]
Sponsorship
This study was supported by a grant PI-0414-2014 from Consejería de Salud (Junta de Andalucía, Spain). Correa-Rodríguez M is a predoctoral fellow (FPU13/ 00143) from the Ministerio de Educación, Cultura y Deporte (Programa de Formación del Profesorado Universitario).Abstract
Background: Osteoporosis individual susceptibility is determined by the interaction of multiple genetic variants
and environmental factors. The aim of this study was to conduct SNP-SNP interaction analyses in candidate genes
influencing heel quantitative ultrasound (QUS) parameter in early adulthood to identify novel insights into the
mechanism of disease.
Methods: The study population included 575 healthy subjects (mean age 20.41; SD 2.36). To assess bone mass QUS
was performed to determine Broadband ultrasound attenuation (BUA, dB/MHz). A total of 32 SNPs mapping to loci
that have been characterized as genetic markers for QUS and/or BMD parameters were selected as genetic markers
in this study. The association of all possible SNP pairs with QUS was assessed by linear regression and a SNP-SNP
interaction was defined as a significant departure from additive effects.
Results: The pairwise SNP-SNP analysis showed multiple interactions. The interaction comprising SNPs rs9340799
and rs3736228 that map in the ESR1 and LRP5 genes respectively, revealed the lowest p value after adjusting for
confounding factors (p-value = 0.001, β (95% CI) = 14.289 (5.548, 23.029). In addition, our model reported others
such as TMEM135-WNT16 (p = 0.007, β(95%CI) = 9.101 (2.498, 15.704), ESR1-DKK1 (p = 0.012, β(95%CI) = 13.641 (2.
959, 24.322) or OPG-LRP5 (p = 0.012, β(95%CI) = 8.724 (1.936, 15.512). However, none of the detected interactions
remain significant considering the Bonferroni significance threshold for multiple testing (p<0.0001).
Conclusion: Our analysis of SNP-SNP interaction in candidate genes of QUS in Caucasian young adults reveal several
interactions, especially between ESR1 and LRP5 genes, that did not reach statistical significance. Although our results do
not support a relevant genetic contribution of SNP-SNP epistatic interactions to QUS in young adults, further studies in
larger independent populations would be necessary to support these preliminary findings.